ADR Awareness Centre

The growing pervasiveness of digital technologies has exposed the entanglements of Human-Computer Interaction (HCI) with its surrounding context, from the immediate vicinity of interfaces to global issues.

Why study this course?

AI has emerged as a critical area of interest to numerous stakeholders across the world.

This document is the first version of the Strategic Research and Innovation Roadmap of the TAILOR project, focussed on Trustworthy Artificial Intelligence through Learning, Optimization and Reasoning.

The main goal of the Handbook of Trustworthy AI (HTAI) is to provide to non-experts, researchers and students, an overview of the problem related to the developing of ethical and trustworthy AI systems.

Recognizing human activity from IoT events is essential for automatic light scene setting. A challenge with IoT systems is the diversity among customers.

This talk will explore the cutting-edge advancements in EdgeAI for biosignal analysis, focusing on innovative algorithms such as Spiking Neural Networks (SNNs), Transformers, and Autoencoders.

This presentation highlights the critical elements defining edge AI solutions’ performance and effectiveness.

In today’s fast-evolving technological landscape, edge AI stands at the forefront of innovation, enabling data processing at the edge, closer to the source of information.

This paper outlines the initial FPGA-centric endeavors within the EdgeAI project, targeting scenarios where extremely constrained power-energy parameters intersect with the demand for high performance and accuracy in executing Artificial Intellige

Presentation detailing our benchmarking of several low cost boards for AI inference on the Edge.
The NN is a small NN that performs 1 channel images classification over 58 categories targeting an industrial application.